An improved data acquisition method for electrical impedance tomography

Isaacson, Cheney and Seager have demonstrated that simultaneously applying trigonometric patterns of current to a circular electrode array optimizes the sensitivity of EIT to inner structure. We have found that it is less desirable to measure voltage at an electrode that also applies a current due to variable contact impedance. In order to preserve the optimum sensitivity while minimizing the effect of electrode artefacts, we have devised an approach where we sequentially apply a current between each individual electrode and a separate, fixed ground while measuring voltages at all other electrodes for each consecutive current impulse. By adding weighted sums of both the applied currents and corresponding measured voltages from individual passes, we can synthesize trigonometric patterns of any spatial frequency. Since only one of the electrodes in any given acquired data set is used as a source, this approach significantly dilutes the effect of contact impedance on the resulting voltage measurements. We present simulated data showing the equivalency between the synthesized and actual trigonometric excitation patterns. In addition, we report experimental data, both in vitro and in vivo, that show improved results using this data acquisition technique.     

Accounting for erroneous electrode data in electrical impedance tomography

An unfortunate occurrence in experimental measurements with electrical impedance tomography is electrodes which become detached or poorly connected, such that the measured data cannot be used. This paper develops an image reconstruction methodology which allows use of the remaining valid data. A finite element model of the EIT difference imaging forward problem is linearized as z = Hx, where z represents the change in measurements and x the element log conductivity changes. Image reconstruction is represented in terms of a maximum a posteriori (MAP) estimate as x = inv(Htinv(Rn) + inv(Rx))Htinv(Rn)z, where Rx and Rn represent the a priori estimates of image and measurement noise crosscorrelations, respectively. Using this formulation, missing electrode data can be naturally modelled as infinite noise on all measurements using the affected electrodes. Simulations indicate position error and resolution are close (+/- 10%) to the values calculated without missing electrode data as long as the target was further than 10% of the medium diameter from the affected electrode. Applications of this technique to experimental data show good results in terms of removing artefacts from images.     

A real-time volumetric visualization system for electrical impedance tomography

Three dimensional (3D) electrical impedance tomography (EIT) presents many additional challenges over and above those associated with two dimensional EIT systems. With present two dimensional (2D) systems, tomographs can be reconstructed and displayed on a PC with a standard computer monitor. In addition, using appropriate data acquisition hardware and simple image reconstruction algorithms, it is possible to collect, reconstruct and display volumetric EIT images in real time using parallel processing architectures. The advantages of this 'real-time' capability are many and include the ability to immediately assess the correct functioning of the system and the ability to track patient events and the effect of procedures in real time. Whilst 3D EIT boundary datasets can be collected in real time, their real-time image reconstruction and display presents some computational challenges. This explains why, to date, no real-time solutions have been presented. In addition the use of a standard computer monitor to display 3D volumes is unsatisfactory since not all depth cues are preserved when using this type of 2D display device. We present a system which is capable of displaying 3D EIT datasets in real time and allows interactive modification of the user's viewpoint. This allows the user to fly around (and through) the EIT volumetric dataset.     

Current injection electrodes for electrical impedance tomography

Current conveyors have been identified as a possible component within the current injection electrodes of an electrical impedance tomography system, where accurate current generation or precise measurement of the current injected is required. Several circuit configurations have been investigated through simulation to determine the most suitable to meet the specifications of the EIT system. A bipolar (floating source) circuit configuration employing the use of current conveyors has been designed, which achieves greater than 12 mA output current without saturation, over an accepted body impedance range. Simulations were performed over frequencies in excess of 1 MHz, and the output phase shift was less than 0.15 degrees up to 250 kHz, and 0.6 degrees up to 1 MHz.     

Current source design for electrical impedance tomography

Questions regarding the feasibility of using electrical impedance tomography (EIT) to detect breast cancer may be answered by building a sufficiently precise multiple frequency EIT instrument. Current sources are desirable for this application, yet no current source designs have been reported that have the required precision at the multiple frequencies needed. We have designed an EIT current source using an enhanced Howland topology in parallel with a generalized impedance converter (GIC). This combination allows for nearly independent adjustment of output resistance and output capacitance, resulting in simulated output impedances in excess of 2 Gohms between 100 Hz and 1 MHz. In this paper, the theoretical operation of this current source is explained, and experimental results demonstrate the feasibility of creating a high precision, multiple frequency, capacitance compensated current source for EIT applications.     

A review on electrical impedance tomography for pulmonary perfusion imaging

Although electrical impedance tomography (EIT) for ventilation monitoring is on the verge of clinical trials, pulmonary perfusion imaging with EIT remains a challenge, especially in spontaneously breathing subjects. In anticipation of more research on this subject, we believe a thorough review is called for. In this paper, findings related to the physiological origins and electrical characteristics of this signal are summarized, highlighting properties that are particularly relevant to EIT. The perfusion impedance change signal is significantly smaller in amplitude compared with the changes due to ventilation. Therefore, the hardware used for this purpose must be more sensitive and more resilient to noise. In previous works, some signal- or image-processing methods have been required to separate these two signals. Three different techniques are reviewed in this paper, including the ECG-gating method, frequency-domain-filtering-based methods and a principal-component-analysis-based method. In addition, we review a number of experimental studies on both human and animal subjects that employed EIT for perfusion imaging, with promising results in the diagnosis of pulmonary embolism (PE) and pulmonary arterial hypertension as well as other potential applications. In our opinion, PE is most likely to become the main focus for perfusion EIT in the future, especially for heavily instrumented patients in the intensive care unit (ICU).     

Adaptive mesh refinement techniques for electrical impedance tomography

Adaptive mesh refinement techniques can be applied to increase the efficiency of electrical impedance tomography reconstruction algorithms by reducing computational and storage cost as well as providing problem-dependent solution structures. A self-adaptive refinement algorithm based on an a posteriori error estimate has been developed and its results are shown in comparison with uniform mesh refinement for a simple head model.     

Pseudo-polar drive patterns for brain electrical impedance tomography

Brain electrical impedance tomography (EIT) is a difficult task as brain tissues are enclosed by the skull of high resistance and cerebrospinal fluid (CSF) of low resistance, which makes internal resistivity information more difficult to extract. In order to seek a single source drive pattern that is more suitable for brain EIT, we built a more realistic experimental setting that simulates a head with the resistivity of the scalp, skull, CSF and brain, and compared the performance of adjacent, cross, polar and pseudo-polar drive patterns in terms of the boundary voltage dynamic range, independent measurement number, total boundary voltage changes and anti-noise performance based on it. The results demonstrate that the pseudo-polar drive pattern is optimal in all the aspects except for the dynamic range. The polar and cross drive patterns come next, and the adjacent drive pattern is the worst. Therefore, the pseudo-polar drive pattern should be chosen for brain EIT.     

A method for modelling and optimizing an electrical impedance tomography system

Electrical impedance tomography (EIT) image reconstruction is an ill-posed problem requiring maximum measurement precision. Recent EIT systems claim 60 to 80 dB precision. Achieving higher values is hard in practice since measurements must be performed at relatively high frequency, on a living subject, while using components whose tolerance is usually higher than 0.1%. To circumvent this difficulty, a method for modelling the electronic circuits of an EIT system was developed in order to optimize the circuits and incorporate the model in the reconstruction algorithms. The proposed approach is based on a matrix method for solving electrical circuits and has been applied to the scan-head which contains the front-end electronic circuits of our system. The method is used to simulate the system characteristic curves which are then optimized with the Levenberg-Marquardt method to find optimal component values. A scan-head was built with the new component values and its simulated performance curves were compared with network analyser measurements. As a result of the optimization, the impedance at the operating frequency was increased to minimize the effects of variations in skin/electrode contact impedance. The transconductance and gain frequency responses were also reshaped to reduce noise sensitivity and unintended signal modulation. Integrating the model in the reconstruction algorithms should further improve overall performance of an EIT system.     

Measurement of regional pulmonary oxygen uptake--a novel approach using electrical impedance tomography

Pulmonary oxygen (O(2)) uptake during apnoea results in a fall in lung volume. Given that electrical impedance tomography (EIT) provides reliable data on regional lung volume changes we hypothesized that EIT could be used to measure regional O(2) uptake. A total of 12 lung healthy supine patients were studied. EIT measurements were performed during volume-controlled mechanical ventilation followed by apnoea with the endotracheal tube clamped at end-expiration. Lung function parameters were assessed by spirometry. A device for breath-by-breath monitoring metabolic gas exchange was used to measure global O(2) uptake. Relative impedance changes during ventilation and apnoea were related to the corresponding tidal volumes. Regional O(2) uptake was analysed as absolute values and as a ratio to regional ventilation in two regions of interest (ventral and dorsal). The global O(2) uptake measured by EIT was 208 ± 79 ml min(-1) corresponding to the values obtained by metabolic gas exchange (259 ± 73 ml min(-1); Spearman correlation coefficient: 0.81, p = 0.02). Regional O(2) uptake was significantly higher in the ventral lung region, while the regional O(2) uptake/ventilation ratio showed no significant difference between the regions. In conclusion, our pilot study indicates that EIT holds substantial potential to detect global and regional pulmonary O(2) uptake concordant with a linear lung volume decrease during apnoea.     

Protective ventilation using electrical impedance tomography

Dynamic thoracic EIT is capable of detecting changes of the ventilation distribution in the lung. Nevertheless, it has yet to become an established clinical tool. Therefore, it is necessary to consider application scenarios wherein fast and distinct changes of the tissue conductivities are to be found and also have a clear diagnostic significance. One such a scenario is the artificial ventilation of patients suffering from the acute respiratory distress syndrome (ARDS). New protective ventilation strategies involving recruitment manoeuvres are associated with noticeable shifts of body fluids and regional ventilation, which can quite easily be detected by EIT. The bedside assessment of these recruitment manoeuvres will help the attending physician to optimize treatment. Hence, we performed an animal study of lavage-induced lung failure and investigated if EIT is capable of qualitatively as well as quantitatively monitoring lung recruitment during a stepwise PEEP trial. Additionally, we integrated EIT into a fuzzy controller-based ventilation system which allows one to perform automated recruitment manoeuvres (open lung concept) based on online PaO2 measurements. We found that EIT is a useful tool to titrate the proper PEEP level after fully recruiting the lung. Furthermore, EIT seems to be able to determine the status of recruitment when combining it with other physiological parameters. These results suggest that EIT may play an important role in the individualization of protective ventilation strategies.     

A motion-compensated cone-beam CT using electrical impedance tomography imaging

Cone-beam CT (CBCT) is an imaging technique used in conjunction with radiation therapy. For example CBCT is used to verify the position of lung cancer tumours just prior to radiation treatment. The accuracy of the radiation treatment of thoracic and upper abdominal structures is heavily affected by respiratory movement. Such movement typically blurs the CBCT reconstruction and ideally should be removed. Hence motion-compensated CBCT has recently been researched for correcting image artefacts due to breathing motion. This paper presents a new dual-modality approach where CBCT is aided by using electrical impedance tomography (EIT) for motion compensation. EIT can generate images of contrasts in electrical properties. The main advantage of using EIT is its high temporal resolution. In this paper motion information is extracted from EIT images and incorporated directly in the CBCT reconstruction. In this study synthetic moving data are generated using simulated and experimental phantoms. The paper demonstrates that image blur, created as a result of motion, can be reduced through motion compensation with EIT.     

Dogleg trust-region application in electrical impedance tomography

This paper presents a trust-region implementation for image reconstruction of conductivity changes in electrical impedance tomography. A dogleg trust-region algorithm is applied in different cases to detect abnormalities. The dogleg algorithm approximates a Levenberg-Marquardt step within the trust region of the model function with a quadratic model. The comparison of Levenberg-Marquardt and dogleg algorithms is presented using the reconstructed images. This comparison of two techniques suggests the implementation of the dogleg method could result in the reduction of the execution time to less than 50% of that of the Levenberg-Marquardt algorithm without any quantifiable loss of quality of reconstructed images.     

Excitation patterns in three-dimensional electrical impedance tomography

Electrical impedance tomography (EIT) is a non-invasive technique that aims to reconstruct images of internal electrical properties of a domain, based on electrical measurements on the periphery. Improvements in instrumentation and numerical modeling have led to three-dimensional (3D) imaging. The availability of 3D modeling and imaging raises the question of identifying the best possible excitation patterns that will yield to data, which can be used to produce the best image reconstruction of internal properties. In this work, we describe our 3D finite element model of EIT. Through singular value decomposition as well as examples of reconstructed images, we show that for a homogenous female breast model with four layers of electrodes, a driving pattern where each excitation plane is a sinusoidal pattern out-of-phase with its neighboring plane produces better qualitative images. However, in terms of quantitative imaging an excitation pattern where all electrode layers are in phase produces better results.     

Temporal image reconstruction in electrical impedance tomography

Electrical impedance tomography (EIT) calculates images of the body from body impedance measurements. While the spatial resolution of these images is relatively low, the temporal resolution of EIT data can be high. Most EIT reconstruction algorithms solve each data frame independently, although Kalman filter algorithms track the image changes across frames. This paper proposes a new approach which directly accounts for correlations between images in successive data frames. Image reconstruction is posed in terms of an augmented image x and measurement vector y, which concatenate the values from the d previous and future frames. Image reconstruction is then based on an augmented regularization matrix R, which accounts for a model of both the spatial and temporal correlations between image elements. Results are compared for reconstruction algorithms based on independent frames, Kalman filters and the proposed approach. For low values of the regularization hyperparameter, the proposed approach performs similarly to independent frames, but for higher hyperparameter values, it uses adjacent frame data to reduce reconstructed image noise.     

Numerical modelling errors in electrical impedance tomography

Electrical impedance tomography (EIT) is a non-invasive technique that aims to reconstruct images of internal impedance values of a volume of interest, based on measurements taken on the external boundary. Since most reconstruction algorithms rely on model-based approximations, it is important to ensure numerical accuracy for the model being used. This work demonstrates and highlights the importance of accurate modelling in terms of model discretization (meshing) and shows that although the predicted boundary data from a forward model may be within an accepted error, the calculated internal field, which is often used for image reconstruction, may contain errors, based on the mesh quality that will result in image artefacts.     

A one step image reconstruction algorithm for electrical impedance tomography in three dimensions

The move from two to three dimensions in the study of electrical impedance tomography (EIT) has generated a great increase in computational demands. It is therefore interesting to investigate ways in which this demand can be reduced, and in this paper we have presented some results of one such approach. The NOSER algorithm was introduced some years ago and we have extended it to include more realistic electrode models. The main feature of the method is that by starting from a uniform conductivity distribution many quantities can be pre-calculated.     

A bio-electromechanical imaging technique with combined electrical impedance and ultrasound tomography

Electrical impedance tomography (EIT) seeks to image the electrical conductivity of an object using electrical impedance measurement data at its periphery. Ultrasound reflection tomography (URT) is an imaging modality that is able to generate images of mechanical properties of the object in terms of acoustic impedance changes. Both URT and EIT have the potential to be used in various medical applications. In this paper we focus on breast tumour detection. Both URT and EIT belong to soft field tomography and suffer from the small amounts of available data and the inherently ill-posed nature of the inverse problems. These facts result in limited achievable reconstruction accuracy and resolution. A dual bio-electromechanical tomography system using ultrasound and electrical tomography is proposed in this paper to improve the detection of the small-size tumour. Data fusion techniques are implemented to combine the EIT/URT data. Based on simulations, we demonstrate the improvement of detection of small size anomalies and improved depth detection compared to single modality soft field tomography.     

A method for analyzing electrical impedance spectroscopy data from breast cancer patients

Research on freshly-excised malignant breast tissues and surrounding normal tissues in an in vitro impedance cell has shown that breast tumors have different conductivity and permittivity from normal or non-malignant tissues. This contrast may provide a basis for breast cancer detection using electrical impedance imaging. This paper describes a procedure for collecting electrical impedance spectroscopy data simultaneously and in register with tomosynthesis data from patients. We describe the methods used to analyze the data in order to determine if the electrodes are making contact with the breast of the patient. Canonical voltage patterns are applied and used to synthesize the data that would have resulted from constant voltage patterns applied to each of two parallel mammography plates. A type of Cole-Cole plot is generated and displayed from each of the currents measured on each of the electrodes for each of the frequencies (5, 10, 30, 100 and 300 kHz) of applied voltages. We illustrate the potential usefulness of these displays in distinguishing breast cancer from benign lesions with the Cole-Cole plots for two patients--one having cancer and one having a benign lesion--by comparing these graphs with electrical impedance spectra previously found by Jossinet and Schmitt in tissue samples taken from a variety of patients.